Response Surface Research Articles

Experimental investigation of benzyl alcohol premixing effect on 5E concepts of compression ignition engine powered with lemongrass oil – diesel blend using response surface methodology

Experimental investigation of benzyl alcohol premixing effect on 5E concepts of compression ignition engine powered with lemongrass oil – diesel blend using response surface methodology

Design and study of moving-iron torque motor for two-dimensional proportional servo valve

This paper proposes a novel moving-iron torque motor designed for two-dimensional (2D) valves. The torque motor features a strap spring in place of the traditional return spring, effectively reducing the overall number of springs. The unique design allows the torque motor to return to its circumferential neutral position through the return torque generated by the strap spring. In order to analyze the torque-displacement characteristics of the torque motor, an analytical model is established, and a simulation model is constructed based on the equivalent magnetic circuit method, which takes into account the magnetic leakage at the control coil and the working air gap. In order to select a strap spring that matches the stiffness of the magnetic spring of the torque motor, the structural parameters of the spring are optimized using the response surface method with multi-objective optimization, and finally three springs with different stiffnesses are manufactured according to the optimization results. The experimental results show that the maximum step-up time of the torque motor is 20.6 ms, the maximum step-down time is 21.6 ms, the maximum hysteresis loop is 12.5%, and the maximum linearity is 20%. In order to improve the −3dB cut-off frequency of the torque motor, this paper adopts the current closed-loop control method, and increases the maximum cut-off frequency not exceeding 25 Hz in the open-loop mode to 110 Hz.The hysteresis loop and linearity of the torque motor decrease with the increase of the spring stiffness. The amplitude frequency −3dB cutoff frequency increases with increasing spring stiffness.

Heat transfer optimization using silver nanoparticle-stabilized nanofluids in copper heat pipes: comparative analysis of stabilizing agents

Abstract This study explores the thermal performance of copper heat pipes filled with surface-modified silver nanoparticle-stabilized nanofluids. The aim was to assess the effect of different nanoparticle surface chemistries on key heat transfer parameters such as thermal resistance and heat transfer coefficient (HTC). Five silver nanofluids stabilized by Polyethylene Glycol (PEG), Branched Polyethyleneimine (bPEI), Polyvinylpyrrolidone (PVP), Citrate, and Lipoic Acid were evaluated under heat inputs ranging from 50 W to 90 W and filling ratios of 60% and 70%. K-type thermocouples were used to measure temperature, from which thermal resistance and HTC were calculated. The bPEI-stabilized nanofluid demonstrated the best performance, reducing thermal resistance from 0.0540 °C/W at 50 W to 0.0420 °C/W at 90 W, while increasing HTC from 1680 W/m2 °C to 2320 W/m2 °C. Response Surface Methodology (RSM) confirmed that higher filling ratios and heat inputs significantly enhanced heat transfer. These findings highlight the potential of surface-modified silver nanofluids to improve thermal management systems, particularly in high heat flux applications. Further research is suggested to explore long-term stability and the scalability of these nanofluids for industrial use.

Can Peer Acceptance and Perceptual Accuracy Impact the Effectiveness of Two Formats of a Preventative Intervention on Functional Subtypes of Aggression in Youth?

Coping Power (CP) is an empirically supported school-based intervention for children at risk for aggression. A child's social status with peers and the extent to which they accurately perceive it are important aspects of preadolescent social development that may influence how intervention format affects disruptive behavior outcomes. Further, reactive (RA) and proactive (PA) functional subtypes of aggression have differential relations with peer acceptance. This study is the first to test whether the effects of group (GCP) and individual (ICP) format of CP on RA and PA differed based on children's actual social status (aim 1) and whether they over- or underestimated their acceptance relative to their actual social status (perceptual accuracy; aim 2). This study involved secondary data analyses using a large-scale randomized controlled trial that assigned 360 children ages 9 to 11 (M = 9.74, SD = .62), predominantly male (n = 234, 65%), and Black (n = 273, 75.8%), with elevated levels of aggression to either ICP or GCP condition. Polynomial regression analyses and three-dimensional response surface plots tested and probed significant (p < .05) interactions between either actual acceptance or perceptual accuracy and intervention format on postintervention reactive and proactive aggression. Actual acceptance moderated the effects of GCP on RA, such that those with higher acceptance showed smaller reductions in RA from either preintervention or postintervention to follow-up. Perceptual accuracy also moderated the effects of ICP on PA, with those underestimating their acceptance showing smaller decreases in PA from postintervention to follow-up. These findings provide valuable insights into how children's actual peer acceptance and perceptual accuracy influence CP outcomes for different functional subtypes of aggression based on intervention format, raising important questions about potential mechanisms.

Optimization of Mold Heating Structure Parameters Based on Cavity Surface Temperature Uniformity and Thermal Response Rates

Rapid heating cycle molding technology has recently emerged as a novel injection molding technique, with the uniformity of temperature distribution on the mold cavity surface being a critical factor influencing product quality. A numerical simulation method is employed to investigate the rapid heating process of molds and optimize heating power, with the positions of heating rods as variables. The temperature uniformity coefficient is an indicator used to assess the uniformity of temperature distribution within a system or process, while the thermal response rate plays a crucial role in evaluating the heating efficiency of a heating system. The thermal response rate of the cavity and the temperature uniformity coefficient are set as optimization objectives to define parameter ranges for orthogonal experiments. The findings indicate that the optimal range for the lateral distance L1 is 20–30 mm, for L2 it is 50–70 mm, and for the vertical distance (h) it is 3–8 mm. The response surface multiple regression equation derived from the orthogonal experiment data demonstrates a model prediction error rate of 1.8% and 2.4%. Additionally, by applying particle swarm optimization to the regression equation, the study identifies an optimal scheme that reduces system energy consumption by 12.5%, achieves a thermal response rate of 0.75 k/s, decreases the temperature uniformity coefficient by 44.6%, and lowers the temperature difference by 52.17%. This optimization ensures efficient heating of the mold cavity, reduces energy consumption, and enhances the uniformity of the surface temperature distribution, ultimately improving the surface quality of the products.

The Response Surface Optimization of the Performance of Modified Polyurethane Membranes for Phenol Removal

In this study, polyurethane (PU) filter membranes were modified with MIL-53(Al) in order to improve phenol removal efficiency. First, one-way analysis of variance (ANOVA) was used to determine that modifier dosage and temperature were significant influences, and pH had a small effect. Then, Design-Expert 13 software was used to derive higher-order fitting equations based on Box–Behnken design, and the parameters were optimized by a system of partial differential equations. Finally, the optimized parameters were obtained by solving the system of partial differential equations, and the reproducibility of the experiment was confirmed using a t-test. The results showed that the modified filter membranes significantly enhanced phenol removal efficiency by 93.34%, which verifies the accuracy of the model and the reproducibility of the experiment and provides theoretical basis and data support for the promotion of the modified membrane.

Modeling of CO2 solubility and partial pressure in blended diisopropanolamine and 2-amino-2-methylpropanol solutions via response surface methodology and artificial neural network

In this study, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were developed to estimate the equilibrium solubility and partial pressure of CO2 in blended aqueous solutions of diisopropanolamine (DIPA) and 2-amino-2-methylpropanol (AMP). In this study, several key parameters were analyzed to understand the behavior of the aqueous DIPA/AMP system for CO2 capture. Including DIPA (9–21 wt%), AMP (9–21 wt%), temperature (323.15–358.15 K), pressure (2.140–332 kPa) and CO2 solubility (0.0531–0.8796 mol/mole). The results of the RSM analysis for CO2 solubility indicate that the model demonstrates a strong fit, as evidenced by a Pred-R² of 0.9601, an adjusted R² of 0.9481, and a highly significant F-value of 80.22. The high predicted R² of 0.9601 and 0.9292 values for CO2 solubility and CO2 partial pressure indicate that the predictor variables can explain a substantial amount of the variability in the response variable. The multilayer perceptron (MLP) architecture demonstrated strong correlation capabilities, featuring one hidden layer with 10 and 5 neurons, respectively. Its topology was structured as 4-10-1 for predicting CO2 solubility and 4-5-1 for predicting CO2 partial pressure. The accuracy of the predictions was notably high, with coefficients of determination of 0.99581 for CO2 solubility and 0.99839 for CO2 partial pressure, achieved using the Levenberg-Marquardt algorithm. Upon further analysis, it was concluded that the MLP model exhibited the lowest error rates, with mean square errors of 0.00009085 for CO2 solubility and 0.00316632 for CO2 partial pressure. The findings emphasized that the MLP model not only outperformed the RSM model in accuracy but also demonstrated greater adaptability in handling the intricate variables associated with CO2 solubility and partial pressure in capture technologies.

Characteristics of NO/SO2 generation during coal/steel dust co-firing under multi-factor synergies

ABSTRACT The co-combustion of solid waste and coal in industrial kilns represents the primary method for the treatment of solid waste. This process must address the critical issue of efficiently controlling nitrogen oxides (NO) and sulfur dioxide (SO2) emissions. In this study, we initially conducted combustion experiments using both single-fuel and mixed-fuel configurations involving coal and steel dust. The experimental results indicated a positive correlation between temperature, airflow rate, and NO/SO2 emissions, while the mixing ratios exhibited a negative correlation. A straightforward regression prediction model for NO/SO2 emissions was developed to enhance understanding of the generation characteristics of NO and SO2, notably, the relative deviation from experimental results was merely 3.16%. This model integrates fuel properties with combustion conditions to elucidate the emission characteristics of nitrogen oxides (NO) and sulfur dioxide (SO2) at their source. Finally, Response surface methodology (RSM) was applied to analyze NO/SO2 emissions under varying operating conditions, including temperature (700–900 °C), air flow rate (80–200 mL/min), and mixing ratios (10–50%).The optimal results were observed at a blending ratio of 50%, where nitrogen (N) and sulfur (S) conversion rates decreased by 25% and 23%, respectively. The results of the analyses determined that the key factors affecting NO emissions, in order of influence, are the mixing ratio, temperature, and air flow rate. For SO2 emissions, the order is mixing ratio, air flow rate, and temperature.

Vechur cow milk yoghurt: response surface methodology-based process optimization and storage studies.

In this research article, response surface methodology (RSM) based optimization of three production parameters namely temperature, time and amount of starter culture of Vechur cow milk yoghurt (VCMY) on the basis of sensory evaluation responses comparing cross-bred cow milk yoghurt (CCMY) as the control is reported. The optimized values of production parameters were 2.15 per cent rate of inoculation, 42°C incubation temperature and 4 h incubation period. The optimized product exhibited significantly lower syneresis, a*, b* values and higher L* values than CCMY. Physico-chemical, microbiological, textural and sensory properties of both VCMY and CCMY during room temperature and refrigerated storage were assessed daily until the onset of spoilage (room temperature) or at five day intervals over a period of 15 d (refrigerated). Both room temperature stored products were graded undesirable by the sensory panel upon one day of storage. Significant reduction was observed in the fat, SNF, total solids, protein and pH content and all the tested colour parameters of the optimized product during refrigerated storage. Total viable counts as well as yeast and mould counts and lactic acid bacteria counts of both VCMY and CCMY progressively increased over the 15 d of storage. Significant reductions were observed in the flavour (P < 0.01), body and texture, colour and appearance and overall acceptability (P < 0.05) scores of both the samples over a period of 15 d. During storage, hardness and adhesiveness values showed an increasing trend whereas the cohesiveness showed a decreasing trend. Storage studies revealed significant differences in the acidity, pH, syneresis, tyrosine value, colour parameters and sensorial attributes of both the yoghurt samples. During the 15 d refrigerated storage period, the VCMY exhibited superior technological attributes to CCMY in terms of lower syneresis %, acidity, microbial population, firmer and less cohesive texture, better flavour, colour and appearance scores. Being the first comprehensive study on the utilization of Vechur cow milk for the preparation of yoghurt, the data generated in the current study would provide a solid base for the exploration of fermentation as a means of value addition of milk of this very rare indigenous cattle breed.

Enhanced Tribological Performance of Laser-Textured TiN-Coated Ti6Al4V Alloy Surfaces: A Comparative Study with Untextured Surfaces

Titanium alloy is widely used as a biomaterial due to its strength, lightweight nature, and corrosion resistance. Despite its strength and lightweight nature, its low wear resistance limits its uses in prosthetic components. Laser surface texturing (LST) was used to improve the wear resistance of titanium alloys by creating textured surfaces before applying protective coatings. A biocompatible TiN composite protective coating was applied using physical vapour deposition (PVD) with a thickness of 4 µm. Response surface methodology (RSM) was used to predict the tribological properties by varying input parameters such as material type (TI, T2, T3, and T4), load in N, and sliding velocity in m/s. A pin-on-disc tribometer was used to conduct a unidirectional sliding wear test based on the RSM design. Tribological properties were studied to determine the impact of laser texturing on the bonding strength of the coating. As a result, material type T4 exhibits an improved coefficient of friction and specific wear resistance under varying sliding velocity and load conditions compared to other material types. The study was further supported by an ANSYS simulation, which revealed stress reduction affecting the coefficient of friction and, consequently, wear. The textured surface topography, wear mechanisms, and coating compositions were examined using scanning electron microscopy.

Hybrid Analysis of Biochar Production from Pyrolysis of Agriculture Waste Using Statistical and Artificial Intelligent-Based Modeling Techniques

Biochar is gaining recognition as a sustainable material, with several applications in soil amendment, carbon sequestration, nutrient dynamics, the remediation of organic contaminants from soil, and water filtration. However, understanding its characteristics is limited due to its intricate structure. This study used response surface methodology (RSM) and artificial neural networks (ANNs) to optimize and predict the production of biochar from the pyrolysis of palm kernel shells. To determine how residence time, nitrogen flow rate, and pyrolysis temperature affected biochar production, a Box–Behnken experimental design was employed. The prediction of the biochar yield was modeled using four different models of ANNs: narrow, medium, wide, and optimum. The physicochemical properties of the biochar produced at pyrolysis temperatures ranging from 400 to 800 °C were determined using X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX), nitrogen (N2) physisorption analysis, and field emission scanning electron microscopy (FESEM). With a p-value significantly lower than 0.05, the response surface quadratic model was found to be the most suitable to optimize the biochar yield obtained from the PKS pyrolysis. Biochar production was very sensitive to the three operating parameters: pyrolysis temperature, nitrogen flow rate, and pyrolysis time. With a coefficient of determination (R2) of 0.900, root mean square error (RMSE) of 0.936, and mean absolute error (MAE) of 0.743, the optimized ANN outperformed the other three ANN models tested. When compared to the optimized ANN, the response surface quadratic model with an R2 of 0.989 had better prediction of biochar yield. At optimized experimental conditions for nitrogen flow rate (150.01 mL/min), temperature (799.71 °C), and pyrolysis time (107.61 min), a biochar yield of 37.87% was obtained at a desirability function of 1.

Improving Thermal Performance in Building Heating, Ventilation, and Air Conditioning Systems: A Study of Natural Convection and Entropy in Plus‐Shaped Cavity

ABSTRACTThe impact of building design on energy efficiency has been widely studied, with cavity cooling emerging as an effective solution for indoor thermal comfort, where obstacles within the cavity can enhance fluid flow and improve natural convection heat transfer (HT). This research builds on the principles of cavity cooling for indoor thermal comfort, investigating entropy generation and HT behavior in a unique plus‐shaped cavity containing a cold cylindrical element, analyzed through Computational Fluid Dynamics simulations. The Rayleigh number (Ra) ranges from 103 to 106, with a fixed Prandtl number (Pr) of 0.71, representing air as the working fluid, radius (r) of the cylinder ranges from 0 to 0.1, where r = 0 indicates no cylinder. The results indicate significant shifts in flow structure and temperature distribution across the cavity at varying Ra values, impacting the local and global entropy generation. High Rayleigh numbers lead to enhanced convective flows, intensifying entropy production near the cylinder surface due to steeper thermal gradients and vigorous recirculation zones. The increase in Ra from 103 to 106 leads to an increase in Nuavg from 24.27 to 56.40 for the model without a cold object while from 39.62 to 123.83 for the model with a cold object. Moreover, the maximum enhancement in Nuavg was 137.48% for Ra = 105. Whereas, for the same value of Ra = 105, the maximum increase in Egen and Be was 474.92% and 33.16%, respectively. Also, a new correlation is proposed to calculate Nuavg using response surface methodology. This study offers a comprehensive examination of heat flow characteristics and entropy generation rates in confined geometries, contributing valuable knowledge to thermal management and optimization in systems with internal obstacles.

Experimental study of parameters in micro-photochemical machining using maskless digital projection on flat surfaces of 100Cr6 steel

Photochemical machining (PCM) is a chemical etching process, in which a photoresist agent is used to cover parts of the workpiece that need to be protected from etching. In this study, the main goal is to create a groove on the flat surface of a workpiece made of 100Cr6 steel using the PCM process and to investigate different variables on the dimensional and geometrical accuracy of the groove. The experiments were designed using the response surface method with a central composite methodology, involving 20 experiments and three repetitions. In this study, the effects of different variables such as time of etching, the concentration of ferric chloride (FeCl3) in the etchant solution, and the weight ratio of hydrochloric acid (HCl) to FeCl3 in the etchant solution were investigated on dimensional accuracy such as length and width error and also geometrical accuracy such as out of parallelism, out of squareness, and out of straightness. Results indicate that as the etching duration increases, the length, width, out of straightness, out of parallelism, and out of squareness also increase. This error becomes substantial with longer durations. Also, with an increase in FeCl3 concentration in etchant solution, errors in length and width, out of straightness, out of parallelism, and out of squareness reduce. The optimal variables resulting in the least possible errors were an etching duration of 10.72 minutes (10 minutes and 43 seconds), FeCl3 solution concentration of 599.64 g/L, and a weight ratio of HCl to FeCl3 in the etchant solution of 0.1. The following results on the flat surface were obtained: groove length: 3,056 µm, groove width: 625 µm, groove depth: 48 µm, and surface roughness (Ra): 1.285 µm.

Experimental investigation and optimization of process parameter of abrasive water jet machining (AWJM) on D2 steel

Abrasive water jet machining (AWJM) is the most significant hybrid unconventional machining technique for its exceptional material removal rate (MRR) and surface quality for any type of brittle, ductile, and composite materials with a higher level of precision and accuracy. It has great flexibility in machining for producing complex-shaped parts that can be used in automobile, marine, aerospace, and chemical industries. This study focuses on the application of AWJM for cutting of D2 steel components using silicon carbide (SiC) abrasives. The experiments are conducted following the Box-Behnken Design (BBD) of response surface methodology (RSM) as the design of experiment (DOE) by considering pressure (P), traverse speed (TS), and abrasive flow rate (AFR) as the input factors each with three different levels in obtaining the corresponding outputs, namely MRR and surface roughness (Ra). Finally, the multicriteria decision-making (MCDM), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, is applied to optimize the output values as MRR of 2.757 mm3/sec, and Ra of 1.014 µm.

Extraction and response surface methodology optimization of tungsten and molybdenum from spent fluidized catalytic cracking catalysts

Extraction and response surface methodology optimization of tungsten and molybdenum from spent fluidized catalytic cracking catalysts

Deciphering the nature and statistical optimization of antimicrobial metabolites of two endophytic bacilli

In this study, Allium sativum, garlic, was selected to isolate endophytic bacteria and to evaluate the antimicrobial, antiviral, antioxidant, and cytotoxic activities of their produced metabolites followed by identification of the biosynthetic gene cluster of the antimicrobial metabolites using Oxford Nanopore Technology (ONT). Two bacterial isolates, C6 and C11, were found to have a broad-spectrum antagonistic effect against four standard microbial strains and were molecularly identified using 16 S ribosomal RNA sequence analysis and deposited in a local culture collection as B. velezensis CCASU-C6, and B. subtilis CCASU-C11, respectively. Optimization for the maximum production of antimicrobial metabolites revealed that a four-day incubation period was optimal, with sucrose and tryptone serving as the best carbon and nitrogen sources for the fermentation media. Response surface methodology model using the central composite design was created resulting in a 1.2-fold and 1.8-fold improvement in antimicrobial metabolite(s) production of C6 and C11 isolates, respectively. The optimal production conditions were found to be a temperature of 33 °C, pH of 7, and an agitation rate of 200 rpm for C6 metabolite, and a temperature of 37 °C, pH of 7, and an agitation rate of 250 rpm for C11 metabolite. Both bacterial isolates displayed antioxidant and antiviral activity and mild cytotoxic action. Genomic sequence and antiSMASH analysis showed that the biosynthetic gene clusters of bacillomycin, mycosubtilin, fengycin, and macrolactin H in B. velezensis CCASU-C6 and bacillibactin and Macrolactin H in B. subtilis CCASU-C11 showed 100% conservation.

Solvometallurgical Properties of Choline Chloride-Based Deep Eutectic Solvents for Copper Extraction from Chalcopyrite: Optimization and Analysis

This paper focuses on the solvometallurgical properties of choline chloride-based deep eutectic solvents for copper extraction from chalcopyrite concentrate. The study, conducted with scientific rigor, utilized the response surface methodology to optimize the extraction process and investigate the effects of the temperature and contact time on the copper recovery efficiency. The results showed that the ChCl-EG-Ox solvent at 80 °C and 48 h produced the highest copper recovery rate, exceeding 76%. This underscores the potential of deep eutectic solvents for sustainable metal extraction. Kinetic studies revealed the influence of temperature on dissolution kinetics, with higher temperatures leading to faster reaction rates. The mineralogical analysis demonstrated the changes in the chalcopyrite concentrate after dissolution, while spectroscopy and mass spectrometry highlighted the esterification reactions in the solvent. The study also examined the effects of adding water and heating on the solvent’s behavior, providing insights into the chemical interactions and structural changes. Ultimately, the research demonstrated that ChCl-based deep eutectic solvents present a promising avenue for environmentally friendly and efficient copper extraction processes in the metallurgical industry.

Design and Testing of a Whole-Row Top-Loosening Stem-Clamping Seedling Extraction Device for Hole Tray Seedlings

A combined seedling extraction device was developed that operates by first top loosening and then clamping the stem in order to solve the current issues with automated transplanting technology, such as low seedling extraction efficiency and a high rate of substrate loss. The pepper plug tray seedlings were selected as the experimental subjects for testing the mechanical properties of the stems. The tensile and compressive mechanical properties of the stems were obtained, and the kinematic model of the seedling spacing process and the mechanical model of the seedling clamping process were established. Key parameters of the seedling extraction device were analyzed and calculated, and an automated seedling extraction system was constructed. Using substrate moisture content, seedling age, and extraction frequency as experimental factors, orthogonal tests were conducted. Through variance analysis and 3D response surface analysis, the optimal rounded parameter values were determined: 48% substrate moisture content, 38-day-old seedlings, and a seedling extraction frequency of 60 plants/min. Under these conditions, the seedling extraction success rate was 94.44%, the substrate loss rate was 6.07%, and the seedling damage rate was 4.17%, meeting the requirements for automated seedling extraction.

Investigation of Factors Influencing Solenoid Valve Speed Response Characteristics of the Common Rail Injector

The dynamic injection characteristics of high-pressure common rail fuel injection systems are determined by the speed response performance of the solenoid valve. A simulation model has been established for investigating the influence mechanism and change law of characteristic parameters on speed response characteristics of the solenoid valve. The speed response characteristics of the solenoid valve, including the average opening speed, the average closing speed, the maximum opening speed, and the maximum closing speed, caused by the changes of characteristic parameters such as pre-tightening force of the solenoid valve spring, mass of the solenoid valve moving parts, diameter of the outflow orifice, diameter of the inflow orifice, diameter of the control piston, and pressure in the common rail, have been studied. The correlation analysis of the influence factors is carried out by using the experimental design method based on the response surface model, and the correlation coefficients between each factor and the speed response characteristics of the solenoid valve are obtained. The results show that both single factors and interaction factors of the parameters are correlated with the speed response characteristics of the solenoid valve. The results of this paper can provide a theoretical reference for the design and optimization of the high-pressure common rail injector.

Optimizing Bacterial Protectant Composition to Enhance Baijiu Yeast Survival and Productivity During Spray Drying

The flavor substances produced by the division of baijiu yeast during the winemaking process often determine the quality of white wine, and the difficulty of storing and transporting high-quality baijiu yeast is a bottleneck that restricts the development of China’s baijiu industry. It is widely accepted that drying microorganisms such as baijiu yeast is the best way to improve its storage and transport performance. Spray drying, as one of the most widely used microbial drying processes, with a high efficiency and low cost, is the hot spot of current research in the field of microbial drying, but it has the inherent defect of a low drying survival rate. In order to address this inherent defect, the present study was carried out with a high-quality white wine yeast, Modified Sporidiobolus Johnsonii A (MSJA), as the target. Firstly, an orthogonal experiment, Steep Hill Climbing experiment, and response surface experiment were sequentially designed to optimize the type and amount of protective agent added in the spray-drying process of MSJA. Then, the effects of glutamyl transaminase (TGase) treatment on the drying process of MSJA were revealed with the help of advanced equipment, such as laser particle sizer, environmental scanning electron microscope (ESEM), and Fourier-transform infrared scanner (FTIR). The results showed that the addition of “TGase-treated soybean isolate protein (SPI) + lactic protein (LP)” as an in vitro bacterial protectant and “14.15% trehalose + 7.10% maltose + 14.04% sucrose” TGase treatment can promote the cross-linking of protective proteins, reduce the distance between MSJA bacteria and protective proteins, and increase the glass transition temperature to enhance the protective effect of protective proteins, so as to improve the survival rate of MSJA during spray drying.